COMPMID-3539: Ignore align_corners for scaled size of 1

Scale kernels failed to validate when align_corners is true
for scaled output size 1. Change this behavior to ignoring
align_corners value to be aligned with expected behavior of
higher-level frameworks.

Also the minimum output size generated by the fixture for
Scale kernels is changed to 1.

Change-Id: Ib8e479af8bc43de3780005545f0c53fe195dc22e
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3478
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

4 files changed, 7 insertions, 41 deletions

diff --git a/tests/validation/CL/Scale.cpp b/tests/validation/CL/Scale.cpp
index 50c148dfba..8a010032a3 100644
--- a/tests/validation/CL/Scale.cpp
+++ b/tests/validation/CL/Scale.cpp
@@ -186,23 +186,6 @@ TEST_CASE(AlignedCornerNotSupported, framework::DatasetMode::ALL)
     ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS);
 }
 
-TEST_CASE(InvalidAlignedCornerOutput, framework::DatasetMode::ALL)
-{
-    // Bilinear with aligned corners require at least 2x2 output to prevent overflow.
-    // Also, aligned corners require sampling policy to be TOP_LEFT.
-    constexpr auto interpolation_policy = InterpolationPolicy::BILINEAR;
-    constexpr bool align_corners        = true;
-    constexpr auto sampling_policy      = SamplingPolicy::TOP_LEFT;
-    const auto     invalid_output_shape = TensorShape{ 1, 1, 3, 2 };
-
-    const auto input  = TensorInfo{ default_input_shape, 1, default_data_type, default_data_layout };
-    const auto output = TensorInfo{ invalid_output_shape, 1, default_data_type, default_data_layout };
-    Status     result{};
-
-    result = CLScale::validate(&input, &output, ScaleKernelInfo{ interpolation_policy, default_border_mode, PixelValue(), sampling_policy, default_use_padding, align_corners });
-    ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS);
-}
-
 TEST_CASE(WindowShrink, framework::DatasetMode::ALL)
 {
     const auto input  = TensorInfo{ TensorShape(37U, 37U, 2U), 1, DataType::F32 };
diff --git a/tests/validation/NEON/Scale.cpp b/tests/validation/NEON/Scale.cpp
index f4a9b9df56..a7eb4b2d8d 100644
--- a/tests/validation/NEON/Scale.cpp
+++ b/tests/validation/NEON/Scale.cpp
@@ -244,23 +244,6 @@ TEST_CASE(AlignedCornerNotSupported, framework::DatasetMode::ALL)
     result = NEScale::validate(&input, &output, ScaleKernelInfo{ interpolation_policy, default_border_mode, PixelValue(), sampling_policy, default_use_padding, align_corners });
     ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS);
 }
-
-TEST_CASE(InvalidAlignedCornerOutput, framework::DatasetMode::ALL)
-{
-    // Bilinear with aligned corners require at least 2x2 output to prevent overflow.
-    // Also, aligned corners require sampling policy to be TOP_LEFT.
-    constexpr auto interpolation_policy = InterpolationPolicy::BILINEAR;
-    constexpr bool align_corners        = true;
-    constexpr auto sampling_policy      = SamplingPolicy::TOP_LEFT;
-    const auto     invalid_output_shape = TensorShape{ 1, 1, 3, 2 };
-
-    const auto input  = TensorInfo{ input_shape, 1, default_data_type, default_data_layout };
-    const auto output = TensorInfo{ invalid_output_shape, 1, default_data_type, default_data_layout };
-    Status     result{};
-
-    result = NEScale::validate(&input, &output, ScaleKernelInfo{ interpolation_policy, default_border_mode, PixelValue(), sampling_policy, default_use_padding, align_corners });
-    ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS);
-}
 TEST_SUITE_END() // Validate
 
 template <typename T>
diff --git a/tests/validation/fixtures/ScaleFixture.h b/tests/validation/fixtures/ScaleFixture.h
index 12d9012ece..b7a821fad4 100644
--- a/tests/validation/fixtures/ScaleFixture.h
+++ b/tests/validation/fixtures/ScaleFixture.h
@@ -74,11 +74,8 @@ protected:
 
         constexpr float max_width{ 8192.0f };
         constexpr float max_height{ 6384.0f };
-
-        const bool is_align_corners_used = _align_corners && arm_compute::is_align_corners_allowed(_sampling_policy);
-
-        const float min_width  = is_align_corners_used ? 2.f : 1.f;
-        const float min_height = is_align_corners_used ? 2.f : 1.f;
+        const float     min_width{ 1.f };
+        const float     min_height{ 1.f };
 
         std::mt19937                          generator(library->seed());
         std::uniform_real_distribution<float> distribution_float(_min_scale, _max_scale);
diff --git a/tests/validation/reference/Scale.cpp b/tests/validation/reference/Scale.cpp
index cb4ad6f909..44beabb2d4 100644
--- a/tests/validation/reference/Scale.cpp
+++ b/tests/validation/reference/Scale.cpp
@@ -26,6 +26,7 @@
 
 #include "Utils.h"
 #include "arm_compute/core/utils/misc/Utility.h"
+#include "src/core/utils/ScaleUtils.h"
 
 namespace arm_compute
 {
@@ -46,9 +47,11 @@ SimpleTensor<T> scale_core(const SimpleTensor<T> &in, float scale_x, float scale
     shape_scaled.set(1, (in.shape()[1] + round_value) * scale_y, /* apply_dim_correction = */ false);
     SimpleTensor<T> out(shape_scaled, in.data_type());
 
+    align_corners = align_corners && arm_compute::scale_utils::is_align_corners_allowed_output_shape(out.shape(), DataLayout::NCHW);
+
     // Compute the ratio between source width/height and destination width/height
-    const auto wr = arm_compute::calculate_resize_ratio(in.shape()[0], out.shape()[0], align_corners);
-    const auto hr = arm_compute::calculate_resize_ratio(in.shape()[1], out.shape()[1], align_corners);
+    const auto wr = arm_compute::scale_utils::calculate_resize_ratio(in.shape()[0], out.shape()[0], align_corners);
+    const auto hr = arm_compute::scale_utils::calculate_resize_ratio(in.shape()[1], out.shape()[1], align_corners);
 
     const auto width  = static_cast<int>(in.shape().x());
     const auto height = static_cast<int>(in.shape().y());